GEOMATIK, cilt.6, sa.1, ss.31-43, 2021 (ESCI)
To know the climate characteristics allows the determination of borders with different climate types; this is important in terms of ensuring the sustainable use of regional resources and direction of land use plans. The determination of climatic boundaries may also serve as a basis for determining and preventing the effects of climate on property and addressing the use of property on a more planned and controlled framework. In this context, climatic classification methods have been developed to determine climatic boundaries. These methods allow the determination of the regional differences of climate types, the examination of the changes over the years and the establishment of different boundaries to suit the climate types. In this study, requirements that an effective role of climate in property use and establish a foundation at the planning point, the formation of the climate border map of the Black Sea Region (meteorological stations in Artvin, Ordu, Rize, Rize-Pazar, Trabzon, Sebinkarahisar, Akcaabat, Unye, Bafra, Hopa, Giresun and Samsun) was taken as basis. The last 30 years of weather parameters measured at the meteorological station points of the region between 1988 and 2018 were obtained, related to the location and arranged in a database in the Geographical Information System (GIS). Then, meteorological data were evaluated according to Thornthwaite climate classification method and climatic types of meteorological station points were classified. Finally, meteorological points with climate type were subjected to Kriging interpolation method and climate boundary maps reflecting the whole region were produced. The resultant product will reflect the climatic boundaries, and the areas where the property's use in terms of climate will be affected and changed; thus, it will serve as a basis for planning and conservation-oriented property works. In addition, this study will make significant contributions to the future studies of the General Directorate of Meteorology (MGM, 2017) as it is approached from different perspectives in terms of obtaining climate boundaries in the form of raster-based grid network independent of district boundaries.